The present invention relates to techniques for aiding a user in determining the rough scale of a viewed scene in a photo or video at the time of capture, so that a relevant computer-vision algorithm may be tuned accordingly.
Computer vision typically involves computerized acquisition, processing, analysis, and understanding of images in order to obtain information about the real world. Scale estimation is an inherent problem in computer vision. For example, knowing the scale or the range of scales of a viewed scene is a prerequisite for almost any computer vision task. In order to obtain useful information about the image, and the real world represented by the image, the scale of the image must be known. Knowing the scale allows the sizes of objects depicted in the image to be determined.
Typically, computer vision processes are adjusted or tuned in order to improve their accuracy. When tuning arguments for such processes, typically the user edits a configuration file, or controls the parameters through various forms of controls such as slider bars, text fields, etc. These solutions have in common that the user needs to know metric data of the scene in order to determine the appropriate value(s) of the image scale. This is difficult because the average user does not know the image dimensions and/or the dimensions of objects seen in the photo/video. Further, in many fields the operator of the computer vision process may not even be familiar with the concept of scale and resolution.
Accordingly, a need arises for techniques by which the scale of a viewed scene in a photo or video may be determined quickly and easily at the time of capture.